Recently, the technologies in the medical image diagnosis field for fusing IT techniques to the medical techniques are being rapidly developed. Among them, medical ultrasonic waves mainly used in the art are useful for visualizing a tomography-scanned image in real time in order to measure size, structure and pathologic damage of muscles, sinew, internal organs, and organs of a human.
In order to implement a medical image for diagnosis by using medical ultrasonic waves as above, a probe is placed in contact with a target and an ultrasonic wave is generated therefrom, and then the ultrasonic wave reflected from the target is received to compose an image. In other words, if an ultrasonic wave is generated, the sonic wave passes through a medium within a very short time, and when the sonic wave passes between two mediums having different sonic impedances, a reflective wave is generated. At this time, the generated reflective wave is measured to reversely calculate a distance by means of the time taken until the reflected sound returns, thereby generating a medical image for diagnosis.
As medical images for diagnosis are widely used in the medical fields, many users regardless of age or sex have increasing demands to generate and check a medical image for diagnosis using an ultrasonic signal while moving regardless of time and place by means of smart devices broadly propagated. However, in spite of such demands, in case of a smart device which is portable, if an ultrasonic signal is processed using the processing power of a CPU therein, it is difficult to provide an image of a useful frame rate. In particular, even though a GPU (Graphic Processing Unit) is provided in the smart device, the parallel-processing algorithm performed in the GPU such as CUDA, OpenCL or the like under the PC-based environment cannot be equivalently performed in the environment of the smart device.
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